Отрывок: The major key-points for matching are recognized in the image. These key-points are usually chosen by ana- lyzing the edges, corners, blobs or even ridges. The first step of the finding the image key-points is to find the maximum and minimum pixels from all its neighbors. II) Key points localization The edges need to be eliminated. For this reason, a concept of a Harris corner detector is used. A 2×2 Hes- sian matrix (H) is used to compute the principal...
Название : | Copy move forgery detection using key point localized super pixel based on texture features |
Авторы/Редакторы : | Rajalakshmi, C. Germanus, Al.M. Balasubramanian, R. |
Ключевые слова : | copy move segmentation SIFT KLSP |
Дата публикации : | Апр-2019 |
Издательство : | Новая техника |
Библиографическое описание : | Rajalakshmi C, Alex MG, Balasubramanian R. Copy move forgery detection using key point localized super pixel based on texture features. Computer Optics 2019; 43(2): 270-276. DOI: 10.18287/2412-6179-2019-43-2-270-276. |
Серия/номер : | 43;2 |
Аннотация : | The most important barrier in the image forensic is to ensue a forgery detection method such can detect the copied region which sustains rotation, scaling reflection, compressing or all. Traditional SIFT method is not good enough to yield good result. Matching accuracy is not good. In order to improve the accuracy in copy move forgery detection, this paper suggests a forgery detection method especially for copy move attack using Key Point Localized Super Pixel (KLSP). The proposed approach harmonizes both Super Pixel Segmentation using Lazy Random Walk (LRW) and Scale Invariant Feature Transform (SIFT) based key point extraction. The experimental result indicates the proposed KLSP approach achieves better performance than the previous well known approaches. |
URI (Унифицированный идентификатор ресурса) : | https://dx.doi.org/10.18287/2412-6179-2019-43-2-270-276 http://repo.ssau.ru/handle/Zhurnal-Komputernaya-optika/Copy-move-forgery-detection-using-key-point-localized-super-pixel-based-on-texture-features-77078 |
Другие идентификаторы : | Dspace\SGAU\20190524\77078 |
Располагается в коллекциях: | Журнал "Компьютерная оптика" |
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Файл | Описание | Размер | Формат | |
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430215.pdf | Основная статья | 1.26 MB | Adobe PDF | Просмотреть/Открыть |
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